The present invention relates to rule-based systems, e.g., portfolio compliance rule-based systems. Portfolio compliance is a unique challenge because it requires maintenance of potentially millions of aggregations with fast impact analysis of any proposed transaction set. An aggregation is a combination of positions, e.g., positions owned or controlled by a single trader or group of traders, that one can use to ensure compliance with rules such as regulations. A position is the amount of a security either owned (which constitutes a long position) or borrowed (which constitutes a short position).
Because the mapping between proposed transaction sets and a set of affected aggregations is not explicit, a compliance architecture must support an efficient matching, calculation and identification of affected aggregations to provide fast impact analysis and explicit reporting. The mapping is not explicit because the aggregations and the proposed transaction sets are both dynamic, e.g., changing over time. Many of these aggregations are comprised of hundreds or thousands of data values across a variety of data structures and sources.
Investment activity in large firms involves tens of thousands of daily transactions affecting a variety of aggregations. The requirement for effective pre-trade compliance is to quickly identify the impact of each set of transactions without adding delays to the investment process.
Conventional systems have not achieved comprehensive real-time scalable portfolio compliance. Only a small percentage of the portfolio compliance rules (typically less than about 10%) are evaluated in real-time. The large majority of compliance rules are checked only in a post-trade (post-mortem) basis. Such post-mortem checking means that violations are only detected after the fact and millions of dollars are put at risk or wasted in preventable errors. The primary impediment to implementing preventive measures is that current solutions do not provide the performance level and scalability needed to evaluate the status of portfolio compliance as part of real-time investment processes. Moreover, the business challenge is getting worse since most organizations have to deal with increasing volumes. Industry trends towards separately managed accounts and increased market regulation will continue to raise the performance thresholds that compliance solutions need to clear before they can be practically integrated into real-time investment processes.
From a technology perspective, existing devices are based on non-scalable and mostly stateful designs. In addition, prior methods typically restrict their choice of technologies to a small set of programming models. Typically portfolio compliance systems are built on procedural language frameworks (like C++) combined with relational database management systems. These systems do not achieve, and thus a need remains for, practical real-time scalable portfolio compliance.